Triple

T7124536
Position Surface form Disambiguated ID Type / Status
Subject Dimasa language E166026 entity
Predicate closelyRelatedTo P37 FINISHED
Object Kachari language E141283 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Kachari language | Statement: [Dimasa language, closelyRelatedTo, Kachari language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kachari language
Context triple: [Dimasa language, closelyRelatedTo, Kachari language]
  • A. Kharia language
    Kharia language is a Munda language spoken primarily by the Kharia people in eastern India, especially in the states of Jharkhand, Odisha, and Chhattisgarh.
  • B. Karbi language chosen
    The Karbi language is a Tibeto-Burman language spoken primarily by the Karbi people in Northeast India, especially in Assam.
  • C. Achuar-Shiwiar language
    The Achuar-Shiwiar language is a Jivaroan language spoken by the Achuar and Shiwiar Indigenous peoples of the Amazon rainforest in Ecuador and Peru.
  • D. Nyishi language
    The Nyishi language is a Tani (Tibeto-Burman) language spoken primarily by the Nyishi people of Arunachal Pradesh in northeastern India.
  • E. Chenchu language
    The Chenchu language is a Dravidian tribal language spoken by the Chenchu people of India, primarily in the forests of Andhra Pradesh and Telangana.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69c6888350588190870cd552b427a1cd completed March 27, 2026, 1:39 p.m.
NER Named-entity recognition batch_69c6e64c0f688190a9b7482d86c2f033 completed March 27, 2026, 8:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7a331ff988190886bde89035623c0 completed March 28, 2026, 9:45 a.m.
Created at: March 27, 2026, 2:44 p.m.